Sayyad Nojavan

There are types of events called events with high effect and low probability, which have a significant impact on network performance. These types of events are divided into two categories: natural hazards and human events, where human events are physical-cyber-attacks. Because distribution networks are progressing and becoming intelligent, and the penetration points to these networks are increasing, it is necessary to study the system's behavior against physical-cyber-attacks. This behavior is known as a new feature called resiliency. The concept of resiliency can be defined as the temporal performance of a network, including robustness, vulnerability, and recovery. Recently, the issue of resiliency in power and distribution networks has been significantly raised. Still, a comprehensive framework for exploiting distribution networks has yet to be presented against it. The purpose of this article is to present a comprehensive model for the resilient exploitation of the intelligent distribution network against physical-cyber-attacks. Therefore, firstly, the model of resilient network operation in normal mode and without modeling physical-cyber-attacks is presented as a MILP model. Then, considering that physical-cyber-attacks can affect the amount of generation of renewable resources and the consumption loads, from the robust optimization method to model physical-cyber-attacks in the worst conditions, taking into account the variables of the active generation power of the wind and the solar resources and the active and the reactive powers of the load consumption have been used as uncertainty variables. The results show that the resiliency index has a high value despite the abnormal conditions resulting from physical-cyber-attacks. Also, renewable energy resources and storage devices improve the system's efficiency and increase the resiliency index. Then, by providing a resiliency index, the resiliency of the network is calculated in different modes of attacks on the n